Search bioRxiv⌕ Search

Biology subjects

Elghraoui, A.

Publications and source records attributed to Elghraoui, A..

5 recordsLinked to original sources

Hybran: Hybrid Reference Transfer and ab initio Prokaryotic Genome Annotation

De novo assembly has become commonplace for microbial organisms, increasing the demand for reliable genome annotation. Ab initio annotation is not an ideal approach for closely related strains due to suboptimal matching of the short or hypervariable genomic features that reference-based annotation transfer can overcome through identification of conserved synteny. At the same time, reference-based annotation methods leave gaps in the annotation where structural variations introduce unique sequence. We present Hybran, a hybrid reference-based and ab initio prokaryotic genome annotation pipeline that transfers features from a curated reference annotation and supplements unannotated regions with ab initio predictions. It builds on existing tools to create initial annotations using both approaches, then compares and resolves them to produce the hybrid annotation. With this pipeline, full advantage is taken of the communitys experimental efforts on reference strains to propagate as many known features as possible without sacrificing best-effort ab initio predictions for the remaining unannotated loci. Genome annotation performed in this way can facilitate comparative genomics and the investigation of evolutionary dynamics in microbial populations. Hybran is freely available at https://lpcdrp.gitlab.io/hybran

bioinformatics↗

Novel and Reported Compensatory Mutations in rpoABC Associate Specifically with Predominant Mycobacterium tuberculosis Rifampicin Resistance Marker rpoB:S450L

BackgroundRifampicin (RIF) is a key first-line drug used to treat tuberculosis, a pulmonary disease caused by Mycobacterium tuberculosis. However antibiotic resistance to RIF is prevalent despite an apparent fitness cost. RIF resistance is primarily caused by mutations in the RIF resistance determining region in the rpoB gene, at the cost of slower growth in rich media. Compensatory mutations in the genes rpoA and rpoC have been shown to alleviate this fitness cost. These compensatory mutations may explain how RIF resistant strains have spread so rapidly. However, the effect of compensation on transmission is still unclear, partly because of uncertainty over which rpoABC mutations compensate for which RIF resistance markers. ObjectivesWe performed an association study on a globally representative set of 4309 whole genome sequenced clinical M. tuberculosis isolates to identify novel putative compensatory mutations, determine the prevalence of known and previously reported putative compensatory mutations, and determine which RIF resistance markers associate with these compensatory mutations. Results and ConclusionsOnly 20.0% (216/1079) of RIF resistant isolates carried previously reported high-probability compensatory mutations, suggesting existence of other compensatory mutations. Using a strict phylogenetic approach, we identified 18 novel putative compensatory mutations in rpoC, rpoB, and rpoA. Novel and previously reported compensatory mutations were strongly associated with the RIFR marker rpoB:S450L, suggesting compensation may be specific to particular RIFR markers. These findings will aid identification of RIF-resistant M. tuberculosis strains with restored fitness. Such strains pose a greater risk of causing resistant outbreaks.

microbiology↗

Evaluating Impacts of Syntenic Block Detection Strategies on Rearrangement Phylogeny Using Mycobacterium tuberculosis Isolates

AO_SCPLOWBSTRACTC_SCPLOWPhylogenetic inference based on genomic structural variations, that manipulate the gene order and content of whole chromosomes, promises to inform a more comprehensive understanding of evolution. The first challenge in using such data, the incompleteness of available de novo assemblies, is easing as long read technologies enable (near-)complete genome assembly, but methodological challenges remain. To obtain the input to rearrangement-based inference methods, we need to detect syntenic blocks of orthologous sequences, a task that can be accomplished in many ways, none of which are obviously preferable. In this paper, we use 94 reference quality genomes of primarily Mycobacterium tuberculosis (Mtb) isolates as a benchmark to evaluate these methods. The clonal nature of Mtb evolution, the manageable genome sizes, along with substantial levels of structural variation make this an ideal benchmarking dataset. We test several methods for detecting homology and obtaining syntenic blocks, and two methods for inferring phylogenies, comparing them to the standard method that uses substitutions for inferring the tree. We find that not only the choice of methods but also their parameters can impact results, especially among branches with lower support. In particular, a method based on an encoding of adjacencies applied to Cactus-defined blocks was fully compatible with the highly supported branches of the substitution-based tree. Thus, we were able to combine the two trees to obtain a supertree with high resolution utilizing both SNPs and rearrangements. Furthermore, we observed that the results were much less affected by the choice of the tree inference method than by the method used to determine the underlying syntenic blocks. Overall, our results indicate that accurate trees can be inferred using genome rearrangements, but the choice of the methods for inferring the homology matters and requires care.

genomics↗

Resolving the hypotheticome: annotating M. tuberculosis gene function through bibliomic reconciliation and structural modeling

Accurate and timely functional genome annotation is essential for translating basic pathogen research into clinically impactful advances. Here, through literature curation and structure-function inference, we systematically update the functional genome annotation of Mycobacterium tuberculosis virulent type strain H37Rv. First, we systematically curated annotations for 589 genes from 662 publications, including 282 gene products absent from leading databases. Second, we modeled 1,711 under-annotated proteins and developed a semi-automated pipeline that captured shared function between 400 protein models and structural matches of known function on protein data bank, including drug efflux proteins, metabolic enzymes, and virulence factors. In aggregate, these structure- and literature-derived annotations update 940/1,725 under-annotated H37Rv genes and generate hundreds of functional hypotheses. Retrospectively applying the annotation to a recent whole-genome transposon mutant screen provided missing function for 48% (13/27) of under-annotated genes altering antibiotic efficacy and 33% (23/69) required for persistence during mouse TB infection. Prospective application of the protein models enabled us to functionally interpret novel laboratory generated Pyrazinamide-resistant (PZA) mutants of unknown function, which implicated the emerging Coenzyme A depletion model of PZA action in the mutants PZA resistance. Our findings demonstrate the functional insight gained by integrating structural modeling and systematic literature curation, even for widely studied microorganisms. Functional annotations and protein structure models are available at https://tuberculosis.sdsu.edu/H37Rv in human- and machine-readable formats. IMPORTANCEMycobacterium tuberculosis, the primary causative agent of tuberculosis, kills more humans than any other infectious bacteria. Yet 40% of its genome is functionally uncharacterized, leaving much about the genetic basis of its resistance to antibiotics, capacity to withstand host immunity, and basic metabolism yet undiscovered. Irregular literature curation for functional annotation contributes to this gap. We systematically curated functions from literature and structural similarity for over half of poorly characterized genes, expanding the functionally annotated Mycobacterium tuberculosis proteome. Applying this updated annotation to recent in vivo functional screens added functional information to dozens of clinically pertinent proteins described as having unknown function. Integrating the annotations with a prospective functional screen identified new mutants resistant to a first-line TB drug supporting an emerging hypothesis for its mode of action. These improvements in functional interpretation of clinically informative studies underscores the translational value of this functional knowledge. Structure-derived annotations identify hundreds of high-confidence candidates for mechanisms of antibiotic resistance, virulence factors, and basic metabolism; other functions key in clinical and basic tuberculosis research. More broadly, it provides a systematic framework for improving prokaryotic reference annotations.

genomics↗

PBHoover and CigarRoller: a method for confident haploid variant calling on Pacific Biosciences data and its application to heterogeneous population analysis

MotivationSingle Molecule Real-Time (SMRT) sequencing has important and underutilized advantages that amplification-based platforms lack. Lack of systematic error (e.g. GC-bias), complete de novo assembly (including large repetitive regions) without scaffolding, can be mentioned. SMRT sequencing, however suffers from high random error rate and low sequencing depth (older chemistries). Here, we introduce PBHoover, software that uses a heuristic calling algorithm in order to make base calls with high certainty in low coverage regions. This software is also capable of mixed population detection with high sensitivity. PBHoovers CigarRoller attachment improves sequencing depth in low-coverage regions through CIGAR-string correction.\n\nResultsWe tested both modules on 348 M.tuberculosis clinical isolates sequenced on C1 or C2 chemistries. On average, CigarRoller improved percentage of usable read count from 68.9% to 99.98% in C1 runs and from 50% to 99% in C2 runs. Using the greater depth provided by CigarRoller, PBHoover was able to make base and variant calls 99.95% concordant with Sanger calls (QV33). PBHoover also detected antibiotic-resistant subpopulations that went undetected by Sanger. Using C1 chemistry, subpopulations as small as 9% of the total colony can be detected by PBHoover. This provides the most sensitive amplification-free molecular method for heterogeneity analysis and is in line with phenotypic methods sensitivity. This sensitivity significantly improves with the greater depth and lower error rate of the newer chemistries.\n\nAvailability and ImplementationExecutables are freely available under GNU GPL v3+ at http://www.gitlab.com/LPCDRP/pbhoover and http://www.gitlab.com/LPCDRP/CigarRoller. PBHoover is also available on bioconda: https://anaconda.org/bioconda/pbhoover.\n\nContactfaramarz@sdsu.edu

bioinformatics↗